Abdurauf Fitrat's term-formation principles and the semantic-functional adaptation of artificial intelligence terms into Uzbek

This article compares Abdurauf Fitrat’s principles of terminology formation with contemporary strategies for adapting English artificial intelligence terminology into Uzbek. Its objective is to develop qualitative criteria for evaluating terminological equivalents in relation to meaning, linguistic structure, and communicative use. The material comprises seven selected expressions: artificial intelligence, machine learning, deep learning, neural network, prompt, chatbot, and large language model. Comparative, componential, word formation, and functional pragmatic methods are employed. The analysis distinguishes calquing, direct borrowing, hybrid nomination, and descriptive rendering. It shows that formal similarity to an English source expression does not necessarily guarantee conceptual accuracy or accessibility for readers. The interpretation of prompt depends on context. Fitrat’s linguistic legacy is treated as a historical comparative perspective rather than direct evidence of continuity with digital terminology. A four criterion assessment framework is proposed, covering conceptual precision, structural compatibility, communicative transparency, and terminological consistency. These qualitative conclusions require corpus verification. The framework may inform terminology development.